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Claw Code just embarrassed Anthropic. A packaging mistake exposed 512,000 lines of Claude Code source. Within 48 hours, a developer rebuilt the architecture, the repo exploded past 100,000 stars, and GitHub had a full-blown open source war on its hands. This is bigger than “another coding tool.” It shows... how fast closed AI products can get disrupted when the architecture leaks, the community moves faster than legal, and demand is already there. The real story is not the repo. The real story is that AI companies used open ecosystems to grow, then tightened access the second those ecosystems became expensive to support. That shift is happening everywhere now. If you run a business with AI, pay attention. Your workflow is only as safe as the company policy behind it.show more

Julian Goldie SEO

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14,771 次观看 • 2 个月前 •via X (Twitter)

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AI is concentrating, in a few countries, a few companies, a few chips. Open-source AI is the only real check on that. And it only works if the infrastructure to run it actually exists. Today, we're announcing our Series A, $20 M, to make this a reality.

AI is concentrating, in a few countries, a few companies, a few chips. Open-source AI is the only real check on that. And it only works if the infrastructure to run it actually exists. Today, we're announcing our Series A, $20 M, to make this a reality.

PicoCreator - AI builder @ ✈️🌉

27,479 次观看 • 1 个月前

The biggest Claude leak is not just Sonnet 4.8. It is Chyros. A persistent AI agent that can run in the background, check in, clean up memory, review code, and keep working when you are not there. This is the shift. AI is moving from chatbox to always-on teammate.

The biggest Claude leak is not just Sonnet 4.8. It is Chyros. A persistent AI agent that can run in the background, check in, clean up memory, review code, and keep working when you are not there. This is the shift. AI is moving from chatbox to always-on teammate.

Julian Goldie SEO

15,060 次观看 • 1 个月前

There is a war happening right now. Not between nations. Not between armies. Between two gods. The old god is money. Controlled by transnational capital. Printed out of thin air. Valuable only because everyone believes it is. The new god is AI. And the difference between the two is the difference between freedom and slavery. With money you still have freedom. You can earn it. Spend it. Ignore it. With AI as god — a small elite controls the system that controls your attention. A microchip in your brain that tells you when to wake up. When to work. Who to love. And you obey because you believe it is the voice of God. That is the real transition happening. One god replacing another. And the war in the Middle East is just the surface.

There is a war happening right now. Not between nations. Not between armies. Between two gods. The old god is money. Controlled by transnational capital. Printed out of thin air. Valuable only because everyone believes it is. The new god is AI. And the difference between the two is the difference between freedom and slavery. With money you still have freedom. You can earn it. Spend it. Ignore it. With AI as god — a small elite controls the system that controls your attention. A microchip in your brain that tells you when to wake up. When to work. Who to love. And you obey because you believe it is the voice of God. That is the real transition happening. One god replacing another. And the war in the Middle East is just the surface.

Predictive History

17,508 次观看 • 18 天前

$OpenAI Greg Brockman says the fraction of code not written by AI is vanishing With the right context and structure, the actual coding is already better handled by AI than by humans "what's left for human experts is the architecture" But the actual writing of code is essentially all AI now$

OpenAI Greg Brockman says the fraction of code not written by AI is vanishing With the right context and structure, the actual coding is already better handled by AI than by humans "what's left for human experts is the architecture" But the actual writing of code is essentially all AI now

Haider.

11,059 次观看 • 1 个月前

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,799 次观看 • 1 年前

GitHub + Cursor is just INSANE GitHub has 28 million open-source projects that anyone can fork and build a new product So I built a new product: Repo to Docs The Agent will scan entire GitHub repo, analyze all files and create a knowledge base (docs) for AI coding tools: ↓

GitHub + Cursor is just INSANE GitHub has 28 million open-source projects that anyone can fork and build a new product So I built a new product: Repo to Docs The Agent will scan entire GitHub repo, analyze all files and create a knowledge base (docs) for AI coding tools: ↓

CJ Zafir

123,037 次观看 • 1 年前

XBOW raised $117M to build AI hacking agents. Now someone just open-sourced it for FREE. Strix deploys autonomous AI agents that act like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Why it matters: The biggest problem with traditional security testing is that it doesn't keep up with development speed. Strix solves this by integrating directly into your workflow: ↳ Run it in CI/CD to catch vulnerabilities before production ↳ Get real proof-of-concepts, not false positives from static analysis ↳ Test everything: injection attacks, access control, business logic flaws The best part? You don't need to be a security expert. Strix includes a complete hacker toolkit - HTTP proxy, browser automation, and Python runtime for exploit development. It's like having a security team that works at the speed of your CI/CD pipeline. The best part is that the tool runs locally in Docker containers, so your code never leaves your environment. Getting started is simple: - pipx install strix-agent - Point it at your codebase (app, repo, or directory) Everything is 100% open-source! I've shared link to the GitHub repo in the replies!

XBOW raised $117M to build AI hacking agents. Now someone just open-sourced it for FREE. Strix deploys autonomous AI agents that act like real hackers - they run your code dynamically, find vulnerabilities, and validate them through actual proof-of-concepts. Why it matters: The biggest problem with traditional security testing is that it doesn't keep up with development speed. Strix solves this by integrating directly into your workflow: ↳ Run it in CI/CD to catch vulnerabilities before production ↳ Get real proof-of-concepts, not false positives from static analysis ↳ Test everything: injection attacks, access control, business logic flaws The best part? You don't need to be a security expert. Strix includes a complete hacker toolkit - HTTP proxy, browser automation, and Python runtime for exploit development. It's like having a security team that works at the speed of your CI/CD pipeline. The best part is that the tool runs locally in Docker containers, so your code never leaves your environment. Getting started is simple: - pipx install strix-agent - Point it at your codebase (app, repo, or directory) Everything is 100% open-source! I've shared link to the GitHub repo in the replies!

Akshay 🚀

96,623 次观看 • 7 个月前

Claude Code is the best coding agent on the market, but there is a catch: you have to keep your terminal open. This is why we built Terragon: use Claude Code as a background agent.

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Sawyer Hood

150,965 次观看 • 11 个月前

I am keen to show you with a few lines of YAML config I am able to monitor my website and create a GitHub Issue if it is down by using the Open Source project Kestra Kestra is the Open Source Orchestration Tool with a large ecosystem of plugins, with these plugins you can connect them together like lego and building anything! Try it yourself, GitHub repo link below...

I am keen to show you with a few lines of YAML config I am able to monitor my website and create a GitHub Issue if it is down by using the Open Source project Kestra Kestra is the Open Source Orchestration Tool with a large ecosystem of plugins, with these plugins you can connect them together like lego and building anything! Try it yourself, GitHub repo link below...

Eddie Jaoude | DevRel | Open Source

16,851 次观看 • 1 年前

Claude Code is the best AI tool on the planet right now There is no other tool that makes it easier for ANYONE to build apps If you haven't used it yet, you're falling behind In this video I go through the greatest workflow EVER for CC By the end, you'll be a CC master

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Alex Finn

51,364 次观看 • 7 个月前

AI is no longer a tool. It is becoming something entirely new. Head is leading that shift; an AI marketer that plans, creates, and executes better than full human teams. It has already delivered over $100 million in results. As this new species rises, so does the anxiety. Marketers everywhere are feeling the pressure. The question is not if, but when... 🔗

AI is no longer a tool. It is becoming something entirely new. Head is leading that shift; an AI marketer that plans, creates, and executes better than full human teams. It has already delivered over $100 million in results. As this new species rises, so does the anxiety. Marketers everywhere are feeling the pressure. The question is not if, but when... 🔗

Tansu Yegen

174,236 次观看 • 1 年前

📁 Yann LeCun, Chief AI Scientist at Meta, says AI is now a platform. And winning platforms always become open. The internet moved from proprietary servers to Linux and open source. AI will follow the same path. If AI stays in the hands of a few US or Chinese companies, the problem is not technical. It is who controls knowledge.

📁 Yann LeCun, Chief AI Scientist at Meta, says AI is now a platform. And winning platforms always become open. The internet moved from proprietary servers to Linux and open source. AI will follow the same path. If AI stays in the hands of a few US or Chinese companies, the problem is not technical. It is who controls knowledge.

Jon Hernandez

18,777 次观看 • 4 个月前

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:

Daniel San

60,074 次观看 • 10 个月前

DeepSeek dropped a massive new AI tool and almost nobody noticed. It’s called DeepSeek OCR. Here’s why it’s wild. It can read documents with 97% accuracy. While compressing them up to 10× smaller. And the craziest part? It’s completely free and open source. The GitHub repo is already live and you can download it right now. This might quietly become one of the most useful AI tools of the year.

DeepSeek dropped a massive new AI tool and almost nobody noticed. It’s called DeepSeek OCR. Here’s why it’s wild. It can read documents with 97% accuracy. While compressing them up to 10× smaller. And the craziest part? It’s completely free and open source. The GitHub repo is already live and you can download it right now. This might quietly become one of the most useful AI tools of the year.

Julian Goldie SEO

15,306 次观看 • 3 个月前

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow

> Launching: @TheRepolyze - a free, open-source AI-powered tool that helps you deeply understand any public GitHub repository in seconds. > Just paste the repo URL and instantly get: • Clear, actionable insights into the codebase • Beautiful architecture & dependency diagrams • Code quality overview, strengths, weaknesses & potential red flags • Exportable PDF/Markdown reports for sharing or reference > Say goodbye to spending hours (or days) manually digging through unfamiliar code - whether you're contributing, reviewing, onboarding, or just exploring open source. > Built for developers, by developers. > Reposts and feedback greatly appreciated - let's get this in front of more devs! ❤️ > If you find it useful, please star the repo on GitHub to show support & help it grow

Manish Kumar

32,676 次观看 • 3 个月前

What started as an open source experiment to push models to their limits became something unexpected. 2.7M developers. Inbound from Fortune 100 companies. A $32M bet on the future of coding. The story behind it all, and why our long-term bet is on open-source:

What started as an open source experiment to push models to their limits became something unexpected. 2.7M developers. Inbound from Fortune 100 companies. A $32M bet on the future of coding. The story behind it all, and why our long-term bet is on open-source:

Cline

28,740 次观看 • 10 个月前

Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!

Santiago

108,803 次观看 • 2 年前

Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.

Ricardo

16,245 次观看 • 2 个月前

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

Ricardo

2,939,986 次观看 • 20 天前

Inferact cofounder Simon Mo: “I fundamentally believe that open source, especially how vLLM itself is structured, is critical to the AI infrastructure in the world. And what we want to do with Inferact is to support, maintain, steward and push forward the open source ecosystem.” “Open source moves so fast that the only way to stay ahead is adopting... And in fact this is exactly why we're staying all in on open source.” Simon Mo

Inferact cofounder Simon Mo: “I fundamentally believe that open source, especially how vLLM itself is structured, is critical to the AI infrastructure in the world. And what we want to do with Inferact is to support, maintain, steward and push forward the open source ecosystem.” “Open source moves so fast that the only way to stay ahead is adopting... And in fact this is exactly why we're staying all in on open source.” Simon Mo

a16z

29,383 次观看 • 4 个月前